| Demand of the question Introduction. What is deep learning technology? Body. Potential applications of deep learning. Conclusion. Conclusion. |
Deep learning is a machine learning technique in which computers learn by examples. Deep learning is a key technology behind driverless cars, enabling them to recognize a stop sign, or to distinguish a pedestrian from a lamppost.
Potential Applications of deep learning:
- Self Driving Cars: Deep learning technology is being employed in self driving cars. It allow cars to learn roads, paths, stop signs, vehicle in front or back using proximity sensors, cameras etc allowing it to drive by itself.
- Voice recognition:
- Deep learning is very successful in voice recognition technology.
- All major commercial speech recognition systems (e.g. Microsoft Cortana, Skype Translator, Amazon Alexa, Google Now, Apple Siri, etc.) are based on deep learning.
- Image recognition:
- Deep learning based image recognition produce more accurate results.
- Deep learning based vehicles now interpret 360° camera views.
- Language translation: Deep learning has helped in improving machine translation. Google Translate uses deep learning technology.
- Pharmaceutical applications: A large number of drugs fail to get regulatory approval.
- These failures are caused by insufficient efficacy, undesired interactions or toxic effects.
- Researchers have uses deep learning to reduce such failures.
- Predicting Earthquakes and weather forecasting: Harvard scientists used Deep Learning in predictions of earthquakes.
- Deep Learning improved calculation time by 50,000%.
- Also deep learning has potential application in developing accurate weather forecast models.
- Bioinformatics: Deep Learning is used in bioinformatics to predict gene related functions. Deep learning has also showed efficacy in healthcare.
- Healthcare application: Deep learning has been used in medical applications such as cancer cell classification, lesion detection, organ segmentation and image enhancement.
- Advertising: It has been used by both publishers and advertisers to increase the relevancy of their ads and boost the return on investment of their advertising campaigns.
- Financial fraud detection:
- Deep learning is used in financial fraud detection and anti-money laundering.
- Deep learning system can recognize relationships and similarities between data and learn to detect anomalies or classify and predict specific events.
Deep Learning is changing the way we look at technologies. Machines can now recognize objects and translate speech in real time. Deep learning applications are already making an impact in our life. With time it’s application will only grow. Indian industry should start exploring deep technology in various fields.
